F21 Cag-dependent huntington's disease patterns over decades: the track-hd and track-on studies. (September 2018) - Langbehn, Douglas
Abstract : Background: In HD, the dependency of onset-age of overt disease on CAG expansion length is well-studied. However, the relationship between CAG length and lifetime trajectory is less well characterized. Aims: To capture the decades-long early progression of Huntington's Disease (HD), its dependence on CAG expansion length, and to evaluate whether progression could be well-represented by clinical and imaging summary measures. Methods: Using the combined longitudinal TRACK-HD and Track-On studies (n=290 CAG-expanded, 153 controls), we used principal component analysis to assess common patterns among CAG-expanded participants, who ranged at study entry from presymptomatic adults to those with stage II disease. We modelled these patterns' interrelationships, dependencies on CAG repeat-length and age, and association with total functional capacity decline. Results: Nominally cognitive and motor measures are highly correlated and have similar CAG- dependent relationships to age; a composite summary score accounted for 67.6% of the combined variance. This score was well-approximated by combining just three items (Total Motor Score, Symbol Digit Modalities Test, and Stroop Word-Reading) from the Unified Huntington's Disease Rating Scale. For either score, initial progression age and later acceleration were highly CAG-dependent, with accelerating beginning in the pre-diagnostic years and continuing through stage II disease. In contrast, we observed three distinct patterns among brain measure changes. A basal ganglia pattern showed considerable change in even the youngest participants, but minimal acceleration with aging. Each clinical and brain summary score strongly predicted the onset and rate of TFC decline. Conclusions: Summary measures of function and brain loss characterize HD progression across the disease span. Similar to HD clinical onset, we show that CAG length strongly predicts the rate of decline throughout late pre-diagnosis and early diagnosis.